Martin White

Martin White, Ph.D.

I am a Chief Scientist at Booz Allen Hamilton. I am also an Adjunct Lecturer in the Department of Computer Science at William & Mary. My research concerns applications of machine learning to software engineering.

Publications

M. Tufano, C. Watson, G. Bavota, M. Di Penta, M. White, and D. Poshyvanyk. Learning how to mutate source code from bug-fixes. In Proceedings of the 35th IEEE International Conference on Software Maintenance and Evolution, ICSME ’19, p. 301–312.

M. Tufano, C. Watson, G. Bavota, M. Di Penta, M. White, and D. Poshyvanyk. An empirical study on learning bug-fixing patches in the wild via neural machine translation. In Transactions on Software Engineering and Methodology, TOSEM ’19, p. 19:1–19:29.

M. White, M. Tufano, M. Martínez, M. Monperrus, and D. Poshyvanyk. Sorting and transforming program repair ingredients via deep learning code similarities. In Proceedings of the 26th IEEE International Conference on Software Analysis, Evolution and Reengineering, SANER ’19, p. 479–490.

M. Tufano, C. Watson, G. Bavota, M. Di Penta, M. White, and D. Poshyvanyk. An empirical investigation into learning bug-fixing patches in the wild via neural machine translation. In Proceedings of the 33rd IEEE/ACM International Conference on Automated Software Engineering, ASE ’18, p. 832–837.

M. Tufano, C. Watson, G. Bavota, M. Di Penta, M. White, and D. Poshyvanyk. Deep learning similarities from different representations of source code. In Proceedings of the 15th Working Conference on Mining Software Repositories, MSR ’18, p. 542–553.

M. White, M. Tufano, C. Vendome, and D. Poshyvanyk. Deep learning code fragments for code clone detection. In Proceedings of the 31st IEEE/ACM International Conference on Automated Software Engineering, ASE ’16, p. 87–98.

M. White. Deep representations for software engineering. In Proceedings of the 37th International Conference on Software Engineering, volume 2 of ICSE ’15, p. 781–783.

M. White, M. Linares-Vásquez, P. Johnson, C. Bernal-Cárdenas, and D. Poshyvanyk. Generating reproducible and replayable bug reports from Android application crashes. In Proceedings of the 23rd International Conference on Program Comprehension, ICPC ’15, p. 48–59.

M. White, C. Vendome, M. Linares-Vásquez, and D. Poshyvanyk. Toward deep learning software repositories. In Proceedings of the 12th Working Conference on Mining Software Repositories, MSR ’15, p. 334–345.

M. Linares-Vásquez, M. White, C. Bernal-Cárdenas, K. Moran, and D. Poshyvanyk. Mining Android app usages for generating actionable GUI-based execution scenarios. In Proceedings of the 12th Working Conference on Mining Software Repositories, MSR ’15, p. 111–122.

Contact Information

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